Background Whole exome sequencing (WES) is a cost-effective method that identifies clinical variants but it demands accurate variant caller tools. Currently available tools have variable accuracy in predicting specific clinical variants. But it may be possible to find the best combination of aligner-variant caller tools for detecting accurate single nucleotide variants (SNVs) and small insertion and deletion (InDels) separately. Moreover, many important aspects of InDel detection are overlooked while comparing the performance of tools, particularly its base pair length. Results We assessed the performance of variant calling pipelines using the combinations of four variant callers and five aligners on human NA12878 and simulated exome data. We used high confidence variant calls from Genome in a Bottle (GiaB) consortium for validation, and GRCh37 and GRCh38 as the human reference genome. Based on the performance metrics, both BWA and Novoalign aligners performed better with DeepVariant and SAMtools callers for detecting SNVs, and with DeepVariant and GATK for InDels. Furthermore, we obtained similar results on human NA24385 and NA24631 exome data from GiaB. Conclusion In this study, DeepVariant with BWA and Novoalign performed best for detecting accurate SNVs and InDels. The accuracy of variant calling was improved by merging the top performing pipelines. The results of our study provide useful recommendations for analysis of WES data in clinical genomics. Electronic supplementary material The online version of this article (10.1186/s12859-019-2928-9) contains supplementary material, which is available to authorized users.

The whole exome sequencing (WES) is a time-consuming technology in the identification of clinical variants and it demands the accurate variant caller tools. The currently available tools compromise accuracy in predicting the specific types of variants. Thus, it is important to find out the possible combination of best aligner-variant caller tools for detecting SNVs and InDels separately. Moreover, many important aspects of InDel detection are not overlooked while comparing the performance of tools. One such aspect is the detection of InDels with respect to base pair length. To assess the performance of variant (especially InDels) caller in combination with different aligners, 20 automated pipelines were developed and evaluated using gold reference variant dataset (NA12878) from Genome in a Bottle (GiaB) consortium of human whole exome sequencing. Additionally, the simulated exome data from two human reference genome sequences (GRCh37 and GRCh38) were used to compare the performance of the pipelines. By analyzing various performance metrices, we observed that BWA and Novoalign aligners performed better with DeepVariant and SAMtools callers for detecting SNVs, and with DeepVariant and GATK for Indels. Altogether, DeepVariant with BWA and Novoalign performed best. Further, we showed that merging the top performing pipelines improved the accurate variant call set. Collectively, this study would help the investigators to effectively improve the sensitivity and accuracy in detecting specific variants.

Background: Stargardt disease 1 (STGD1; MIM 248200) is a monogenic form of autosomal recessive genetic disease caused by mutation in ABCA4. This gene has a major role in hydrolyzing N-retinylidene-phosphatidylethanolamine to all-trans-retinal and phosphatidylethanolamine. The purpose of this study is to identify the frequency of putative disease-causing mutations associated with Stargardt disease in a South Indian population. Methods: A total of 28 clinically diagnosed Stargardt-like phenotype patients were recruited from south India. Ophthalmic examination of all patients was carefully carried out by a retina specialist based on the stages of fundus imaging and ERG grouping. Genetic analysis of ABCA4 was performed for all patients using Sanger sequencing and clinical exome sequencing. Results: This study identified disease-causing mutations in ABCA4 in 75% (21/28) of patients, 7% (2/28) exhibited benign variants and 18% (5/28) were negative for the disease-causing mutation. Conclusion: This is the first study describing the genetic association of ABCA4 disease-causing mutation in South Indian Stargardt 1 patients (STGD1). Our findings highlighted the presence of two novel missense mutations and an (in/del, single base pair deletion & splice variant) in ABCA4. However, genetic heterogeneity in ABCA4 mutants requires a larger sample size to establish a true correlation with clinical phenotype.

Multiple studies have identified several pathogenic variants, majorly contribute to the pathogenesis of primary open-angle glaucoma (POAG). However, these genetic factors can only explain 5-6% of POAG. To identify pathogenic variants associated with POAG by using Whole Exome Sequencing (WES) data of an Egyptian origin of a large family with POAG settled in South India. We recruited a large five-generation family with a positive family history of POAG from Kayalpatanam, Tamil Nadu, India who basically from Egyptian origin. All participants had a comprehensive ocular evaluation (367 study subjects, including 22 POAG and 20 Suspects). We performed WES for 16 samples (9 POAG and 7 controls). We identified one novel potential pathogenic variants, with low-frequency and several pathogenic variants. The heterozygous pathogenic variant c.G3719A in the RPGR-interacting domain of RPGRIP1 gene is segregated in six POAG cases, which may affect the function of RPGR protein complex. In contrast, the RPGRIP1 variant (G1240E) is relatively common in most populations especially in Africans. Furthermore, we identified a novel c.A1295G variant in Rho guanine nucleotide exchange factors Gene 40 (ARHGEF40) and in Retinitis Pigmentosa GTPase regulator (RPGR) gene, may affect the intraocular pressure regulation by altering the RhoA signaling pathway through RPGR protein complex. Moreover, it is difficult to determine the population frequency for this variant. Even though our study reports rare pathogenic variants in multiple genes and pathways associated in the large family with POAG, epigenetic changes and copy number variations may explored to understand the incredibly complexity of the POAG pathogenesis.

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